Knowledge Graph Construction for Foreign Military Unmanned Systems

被引:2
作者
Chen, Yilin [1 ]
Wang, Jingting [1 ]
Zhu, Shutong [1 ]
Gu, Yuang [1 ]
Dai, Haoyu [1 ]
Xu, Jingyi [1 ]
Zhu, Yipeng [1 ]
Wu, Tianxing [1 ]
机构
[1] Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China
来源
CCKS 2022 - EVALUATION TRACK | 2022年 / 1711卷
关键词
Unmanned systems; Knowledge extraction; Knowledge graph; Knowledge graph completion;
D O I
10.1007/978-981-19-8300-9_14
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Unmanned systems have become a significant component of modern military forces and play a more and more important role in various military operations. It mainly consists of four major domains which are unmanned aerial system (UAS), unmanned ground vehicle (UGV), unmanned underwater vehicle (UUV), and unmanned surface vessel (USV). This paper focuses on the construction of a high-quality knowledge graph on foreign unmanned systems and proposes an effective method to complete the construction. The method first analyses the data provided by CCKS2022 evaluation organizers and builds a schema. Then not only data provided are used to construct the knowledge graph but also external data are crawled and extracted as triples under constraints of the schema. After that, entities are aligned and logic rules are also utilized to knowledge graph completion. Finally, the knowledge graph constructed is stored and visualized in the Neo4j database and evaluated by the question-answering tasks. This paper presents our technics for the 13th task of CCKS2022 evaluation (i.e. knowledge graph construction and evaluation on foreign military unmanned systems) and our team win the 3rd place in this task.
引用
收藏
页码:127 / 137
页数:11
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